1. Field of the Invention
The invention relates in general to a system and a method for performing rapid facial recognition, and more particularly to a system which performs distributed processing through the feature recognition modules of a plurality of computing units and their classes allocated and a method for performing rapid facial recognition.
2. Description of the Related Art
Facial recognition, which has attracted a lot of attention from both the academic arena and the industry in recent years, has achieved great performance in the application of public safety and access security control. Comparing with the conventional access security control, the technology of facial recognition has the advantages of better protection, higher efficiency and easier solution to the misplacement of access card. Meanwhile, comparing with other bio-recognition, facial recognition being non-invasive and non-contact is easy for people to be accepted. Particularly, when the user's both hands are occupied and are unable to swipe the access card or input the passwords, the advantages of the facial recognition technology will be appreciated.
A parallel processing block diagram is disclosed in FIG. 2 of US Patent 2007/0091884 A1. Data are divided into two parts and respectively transferred to different computing units for computing. Lastly, the results are transmitted to and displayed at the user end.
The block diagram disclosed in FIG. 1 of US Patent 2007/0091883 A1 differs with the structure disclosed in United States Patent Publication No. US2007/091884 A1 in that data can be exchanged among the computing units engaged in parallel computing. For example, data are transmitted to a target unit from a first unit, then the data are computed by the target unit, and the results are further transmitted to the next unit for subsequent processing until the final result is accomplished. Both the present patent and the previous patent perform distributed processing on a large volume of data at a high speed and balance the work load of different units.
According to the block diagram disclosed in FIG. 1 of U.S. Pat. No. 7,346,186, each image capture unit is equipped with an image processing unit, which analyzes image and then saves or transmits the original data and the result of analysis together to a central control unit. The part of the image processing unit only performs analyzing and processing tasks for the image captured by the image capture device connected thereto without performing the division of labor.
A system and method for rapidly tracking multiple faces are disclosed in FIG. 1 of Taiwan Patent 165076 (corresponding to U.S. Pat. No. 7,003,135). The method uses a face-like region generator to find a face-like region by skin color, motion and silhouette information. A face status checker compares the face-like region with all tracked faces recorded in a face recorder for determining whether the face-like regions are an old faces tracked in a previous frame or possible new faces. Lastly, a face tracking engine performs multiple face tracking according to the new faces and old faces, and the information such as skin color and region provided by the face-like region generator. Before the time-consuming facial recognition is performed, the technology filters the face data by information such as skin color, motion and silhouette, and classifies the face data into old faces (the faces being recognized) and new faces (the faces not yet being recognized), and verifies the new faces only.
A multi-level facial image recognition method is disclosed in FIG. 1 of Taiwan Patent 152862 (corresponding to U.S. Pat. No. 6,697,504). The method uses a quadrature mirror filter to decompose an image into at least two sub-images having different resolution levels by multi-resolution decomposing method. The testing starts with the lowest resolution level. If the face data is unrecognizable at a low resolution level, then the face data is recognized at a higher level of resolution.
As disclosed in FIG. 1 of Taiwan Patent 147927, a camera disposed at a predetermined position obtains face sampling data to identify the position of the face, and further tracks the faces that need to be recognized. Whether the face is an existing face or an abnormal face is determined by sampling and analyzing the face silhouette of the faces at the checking region. Lastly, the determined face image data are stored, and the non-determined abnormal image data are directly transmitted to another set of recognition system.